Research paperEstimating the unsaturated hydraulic conductivity from theoretical models using simple soil properties
References (22)
- et al.
A field study of soil water depletion patterns in presence of growing soy bean roots. I. determination of hydraulic properties of the soil
Soil Sci. Soc. Am. J.
(1975) - et al.
Assesing the suitability of soils with macropores for subsurface liquid disposal
J. Environ. Qual.
(1983) Probability laws for pore size distributions
Soil Sci.
(1966)Relative permeability calculations from size distribution data
Trans. AIME
(1953)- et al.
The permeability of porous materials
- et al.
Relative permeabilities of California cres by the capillary-pressure method. Drilling and production practice
Am. Petrol. Inst.
(1950) - et al.
Factors important in the calculation of hydraulic conductivity
A relation between permeability and size distribution of pores
J. Soil Sci.
(1958)- et al.
Permeability of porous solids
Faraday Soc.
(1961) A new model for predicting the hydraulic conductivity of unsaturated porous media
Water Resour. Res.
(1976)
Hydraulic conductivity of soils: unified approach to the statistical models
Soil Sci. Soc. Am. J.
Cited by (77)
Hydraulic behaviour of sand-biochar mixtures in water and wastewater treatment applications
2022, Journal of HydrologyA simple method for predicting the hydraulic properties of unsaturated soils with different void ratios
2021, Soil and Tillage ResearchUtilizing Splintex 2.0 for estimating the soil hydraulic conductivity curve measured with instantaneous profile method
2020, Soil and Tillage ResearchCitation Excerpt :The predictors sand, silt, clay, and ρb were significantly correlated with θs and m estimated by Splintex 2.0 and with the measured Ks showing the expected physical behavior. Overall, the cross-correlation among VGM parameters and their predictors is complex, as also reported since Vereecken (1995) and Schaap and Leij (2000) and currently declared by Ottoni et al. (2019) and Zhang and Schaap (2019). In this study, the performance of Splintex 2.0 for estimating VGM parameters that compose the soil hydraulic conductivity curve (SHCC), including the saturated hydraulic conductivity (Ks), for four texture groups and a range of bulk densities was evaluated.
Improving unsaturated hydraulic conductivity estimation in soils via percolation theory
2017, GeodermaCitation Excerpt :Accurate estimate of unsaturated hydraulic conductivity K(Sw) is still challenging and of great interest, particularly in two-phase flow and contaminant transport modeling in soils. Various models based on data mining techniques (e.g., Wösten and van Genuchten, 1988; Vereecken et al., 1990; Vereecken, 1995; Schaap and Leij, 1998; Weynants et al., 2009), bundle of straight capillary tubes (e.g., Purcell, 1949; Childs and Collis-George, 1950; Burdine, 1953; Mualem, 1976; Kosugi, 1999), bundle of tortuous capillary tubes (e.g., Yu et al., 2003; Liu et al., 2007; Xu et al., 2013), critical path analysis (e.g., Hunt, 2001; Hunt and Gee, 2002a,b; Hunt, 2004a; Ghanbarian-Alavijeh and Hunt, 2012; Hunt et al., 2013), effective-medium approximations (e.g., Levine and Cuthiell, 1986; Kanellopoulos and Petrou, 1988; Ghanbarian et al., 2016b), percolation theory (e.g., Larson et al., 1981; Heiba et al., 1992; Blunt et al., 1992), pore network models (e.g., Jerauld and Salter, 1990; Blunt and King, 1991; Bakke and Øren, 1997; Raoof and Hassanizadeh, 2012) and lattice-Boltzmann methods (e.g., Hazlett et al., 1998; Ramstad et al., 2010; Zhang et al., 2016) have been developed to estimate K(Sw) from other porous medium characteristics, such as water retention curve (also known as capillary pressure curve), particle-size distribution, porosity, saturated hydraulic conductivity Ks, two- and three-dimensional images, etc. The literature on unsaturated hydraulic conductivity modeling and estimation is vast and extensive.